.png){kind=icon}
返回
Modelling Affect for Horror Soundscapes
.png){kind=icon}
OA
AI
DOI：10.1109/TAFFC.2017.2695460.png)
.png){kind=icon}
.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
The feeling of horror within movies or games relies on the audience's perception of a tense atmosphere-often achieved through sound accompanied by the on-screen drama-guiding its emotional experience throughout the scene or game-play sequence. These progressions are often crafted through an a priori knowledge of how a scene or game-play sequence will playout, and the intended emotional patterns a game director wants to transmit. The appropriate design of sound becomes even more challenging once the scenery and the general context is autonomously generated by an algorithm. Towards realizing sound-based affective interaction in games this paper explores the creation of computational models capable of ranking short audio pieces based on crowdsourced annotations of tension, arousal and valence. Affect models are trained via preference learning on over a thousand annotations with the use of support vector machines, whose inputs are low-level features extracted from the audio assets of a comprehensive sound library. The models constructed in this work are able to predict the tension, arousal and valence elicited by sound, respectively, with an accuracy of approximately 65%, 66% and 72%.
Keyword:
Horror
sonification
tension
crowdsourcing
preference learning
rank annotations
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
9.8
论文数:
1.4K
被引数:
9.1K
机构
引用论文
分享收藏A Cross-Linguistic Perspective on the Acquisition of Causal Connectives and Relations因果连接词和关系习得的跨语言视角OAAI
OAAI分享收藏分享收藏Survey on speech emotion recognition: Features, classification schemes, and databases.png)
PATTERN RECOGNITION
PATTERN RECOGNITIONIF7.6
PREAI
分享收藏Temperature Effect on the Tropospheric Radio Signal Strength for UHF Band at Terengganu, Malaysia
OAAI
OAAI分享收藏
查看更多内容